import streamlit as st
import matplotlib.pyplot as plt
import pandas as pd
import numpy as np

# Set streamlit configuration with wide mode
st.set_page_config(layout="wide")
st.config.set_option("server.enableXsrfProtection", False)

def plot_signal(signal, index):
    # Assuming df is your DataFrame and 'Signal1', 'Signal2', 'Signal3' are your columns
    ch1 = pd.to_numeric(signal[index], errors='coerce')

    # Define the moving average window size
    N = 25

    # Function to calculate moving RMS
    def moving_rms(signal, window_size):
        return np.sqrt(pd.Series(signal).rolling(window=window_size).mean()**2)

    # Calculate moving RMS for each channel
    ch1_rms = moving_rms(ch1, N)

    # Calculate mean and standard deviation of the RMS signals
    mean_ch1_rms = np.mean(ch1_rms)
    std_ch1_rms = np.std(ch1_rms)

    # Print mean and standard deviation values
    st.write(f'Mean of RMS Signal {int(index)}: {mean_ch1_rms:.3f},   Std Dev of RMS Signal 1: {std_ch1_rms:.3f}')
    
    # Plot the RMS signals
    plt.figure(figsize=(15,6))
    plt.plot(ch1_rms, label='Signal 1 RMS')
    plt.title('RMS Signal Values, Moving Average Window Size N=25')
    plt.xlabel('Index')
    plt.ylabel('RMS Value')
    plt.legend()
    st.pyplot(plt.gcf())
    # plt.show()

      
def main():
    st.title('👅Dysphagia Analysis - by ITRI BDL')
    uploaded_file1 = st.file_uploader("Choose the EMG_data CSV file", type="csv")
    uploaded_file2 = st.file_uploader("Choose the time_marker CSV file", type="csv")
    if uploaded_file1 is not None:
        try:
            data1 = pd.read_csv(uploaded_file1, skiprows=[0,1,3,4])
            # st.dataframe(data1)
        except Exception as e:
            st.error(f"Error: {e}")
        
    if uploaded_file2 is not None:    
        try:
            data2 = pd.read_csv(uploaded_file2, skiprows=[0,1])
            # st.dataframe(data2)
        except Exception as e:
            st.error(f"Error: {e}")
            
    # Detect Upload File and choose signal with sidebar menu
    if uploaded_file1 is not None and uploaded_file2 is not None:
        signal = st.sidebar.selectbox('Select EMG Signal', data1.columns)
        st.write(f'You selected: channel {signal}')
        
        # Plot the selected signal
        st.line_chart(data1[signal])
        
        # Analysis button        
        if st.button('Start Analysis'):
            st.write('Analysis started...')
            # Add analysis code here
            plot_signal(data1, signal)
            st.write('Analysis completed...')
    
        
if __name__ == '__main__':
    main()